4.3. mbl.analysis.energy_bounds.EnergyBounds#

class mbl.analysis.energy_bounds.EnergyBounds[source]#

Bases: object

__init__()#

Methods

__init__()

athena_query(n, h[, overall_const, penalty, ...])

query_elements(n, h[, overall_const, ...])

retrieve(n, h[, overall_const, penalty, ...])

Naive setup for energy bounds without considering the effect of truncation errors and finite-size effect.
class Metadata(database: str = 'random_heisenberg', table: str = 'tsdrg')[source]#

Bases: object

Parameters

  • database (str) –

  • table (str) –

Return type

None

database: str = 'random_heisenberg'#
table: str = 'tsdrg'#
__init__(database='random_heisenberg', table='tsdrg')#
Parameters

  • database (str) –

  • table (str) –

Return type

None

classmethod query_elements(n, h, overall_const=1, penalty=0.0, s_target=0, seed=None, chi=None)[source]#
Parameters

  • n (int) –

  • h (float) –

  • overall_const (float) –

  • penalty (float) –

  • s_target (int) –

  • seed (Optional[int]) –

  • chi (Optional[int]) –

classmethod athena_query(n, h, overall_const=1, penalty=0.0, s_target=0, seed=None, chi=None, method=None, boto3_session=None, **kwargs)[source]#
Parameters

  • n (int) –

  • h (float) –

  • overall_const (float) –

  • penalty (float) –

  • s_target (int) –

  • seed (Optional[int]) –

  • chi (Optional[int]) –

  • method (Optional[str]) –

  • boto3_session (Optional[boto3.session.Session]) –

Return type

float

classmethod retrieve(n, h, overall_const=1, penalty=0.0, s_target=0, seed=None, chi=None, boto3_session=None, **kwargs)[source]#

Naive setup for energy bounds without considering the effect of truncation errors and finite-size effect.

Parameters

  • n (int) –

  • h (float) –

  • overall_const (float) –

  • penalty (float) –

  • s_target (int) –

  • seed (Optional[int]) –

  • chi (Optional[int]) –

  • boto3_session (Optional[boto3.session.Session]) –

  • **kwargs – Additional kwargs passed to athena sql query.

Return type

Dict[str, float]

Returns:

Notes

The upside down spectrum (for which we apply -1 to the Hamiltonian) saved on AWS Athena doesn’t restore the original spectrum up to an overall constant.